class_docstr: Main network which does cross-lingual embeddings training
docstr: Runs generator part of GAN
  Arguments:
      sess(tf.session): Tensorflow Session
      local_lr(float): Learning rate
  Returns:
      Returns number of words processed
docstr_tok: ["Runs","generator","part","of","GAN","Arguments",":","sess","(","tf.session",")",":","Tensorflow","Session","local_lr","(","float",")",":","Learning","rate","Returns",":","Returns","number","of","words","processed"]
code: def run_generator(self, sess, local_lr):
      """
      Runs generator part of GAN
      Arguments:
          sess(tf.session): Tensorflow Session
          local_lr(float): Learning rate
      Returns:
          Returns number of words processed
      """
      # Generate random ids to look up
      src_ids = np.random.choice(
          self.vocab_size, self.batch_size, replace=False
      )
      tgt_ids = np.random.choice(
          self.vocab_size, self.batch_size, replace=False
      )
      train_dict = {
          self.generator.src_ph: src_ids,
          self.generator.tgt_ph: tgt_ids,
          self.discriminator.do_ph: 1.0,
          self.lr_ph: local_lr,
      }
      sess.run(self.generator.map_opt, feed_dict=train_dict)
      # Run orthogonalize
      sess.run(self.generator.assign_weight)
      return 2 * self.batch_size
  
imports: from __future__ import print_function, division
  import io
  import os
  import time
  import numpy
  import scipy
  import tensorflow
label_desc: Use image node_id 5 for calling the WordTranslator obj's underlying member method code with example usage: obj.run_generator(sess, local_lr) and returns: unknown